Catalogue of data and platforms at Network GDAC level, including the example of Copernicus In Situ TAC

This document presents catalogue techniques used at network GDAC level to facilitate the discovery of platforms and data files. Some AtlantOS networks are organized as DAC-GDACs that continuously update a catalogue of metadata on observation datasets and platforms: • A DAC is a Data Assembly Centre operating at national or regional scale. It manages data and metadata for its area with a direct link to Scientifics and Operators. The DAC pushes observations to the network GDAC. • A GDAC is a Global Data Assembly Centre. It is designed for a global observation network such as Argo, OceanSITES, DBCP, EGO, Gosud, etc… The GDAC aggregates data and metadata of an observation network, in real-time and delayed mode, provided by DACs.

The Kinome of Pacific Oyster Crassostrea gigas, Its Expression during Development and in Response to Environmental Factors

Oysters play an important role in estuarine and coastal marine habitats, where the majority of humans live. In these ecosystems, environmental degradation is substantial, and oysters must cope with highly dynamic and stressful environmental constraints during their lives in the intertidal zone. The availability of the genome sequence of the Pacific oyster Crassostrea gigas represents a unique opportunity for a comprehensive assessment of the signal transduction pathways that the species has developed to deal with this unique habitat. We performed an in silico analysis to identify, annotate and classify protein kinases in C. gigas, according to their kinase domain taxonomy classification, and compared with kinome already described in other animal species. The C. gigas kinome consists of 371 protein kinases, making it closely related to the sea urchin kinome, which has 353 protein kinases. The absence of gene redundancy in some groups of the C. gigas kinome may simplify functional studies of protein kinases. Through data mining of transcriptomes in C. gigas, we identified part of the kinome which may be central during development and may play a role in response to various environmental factors. Overall, this work contributes to a better understanding of key sensing pathways that may be central for adaptation to a highly dynamic marine environment.

The EMSO-ERIC Pan-European Consortium: Data Benefits and Lessons Learned as the Legal Entity Forms

The European Multidisciplinary Seafloor and water-column Observatory (EMSO) European Research Infrastructure Consortium (ERIC) provides power, communications, sensors, and data infrastructure for continuous, high-resolution, (near-)real-time, interactive ocean observations across a multidisciplinary and interdisciplinary range of research areas including biology, geology, chemistry, physics, engineering, and computer science, from polar to subtropical environments, through the water column down to the abyss. Eleven deep-sea and four shallow nodes span from the Arctic through the Atlantic and Mediterranean, to the Black Sea. Coordination among the consortium nodes is being strengthened through the EMSOdev project (H2020), which will produce the EMSO Generic Instrument Module (EGIM). Early installations are now being upgraded, for example, at the Ligurian, Ionian, Azores, and Porcupine Abyssal Plain (PAP) nodes. Significant findings have been flowing in over the years; for example, high-frequency surface and subsurface water-column measurements of the PAP node show an increase in seawater pCO2 (from 339 μatm in 2003 to 353 μatm in 2011) with little variability in the mean air-sea CO2 flux. In the Central Eastern Atlantic, the Oceanic Platform of the Canary Islands open-ocean canary node (aka ESTOC station) has a long-standing time series on water column physical, biogeochemical, and acidification processes that have contributed to the assessment efforts of the Intergovernmental Panel on Climate Change (IPCC). EMSO not only brings together countries and disciplines but also allows the pooling of resources and coordination to assemble harmonized data into a comprehensive regional ocean picture, which will then be made available to researchers and stakeholders worldwide on an open and interoperable access basis.

Description of the Argo GDAC File Checks: Data Format and Consistency Checks

Every Argo data file submitted by a DAC for distribution on the GDAC has its format and data consistency checked by the Argo FileChecker. Two types of checks are applied: 1. Format checks. Ensures the file formats match the Argo standards precisely. 2. Data consistency checks. Additional data consistency checks are performed on a file after it passes the format checks. These checks do not duplicate any of the quality control checks performed elsewhere. These checks can be thought of as “sanity checks” to ensure that the data are consistent with each other. The data consistency checks enforce data standards and ensure that certain data values are reasonable and/or consistent with other information in the files. Examples of the “data standard” checks are the “mandatory parameters” defined for meta-data files and the technical parameter names in technical data files. Files with format or consistency errors are rejected by the GDAC and are not distributed. Less serious problems will generate warnings and the file will still be distributed on the GDAC. Reference Tables and Data Standards: Many of the consistency checks involve comparing the data to the published reference tables and data standards. These tables are documented in the User’s Manual. (The FileChecker implements “text versions” of these tables.)